Search engines have become widely used by many in society. Generally, a search engine is an information retrieval system designed to help find information stored on a computer system, network, and the like. Search engines primarily function by reducing the time required to find information and/or the amount of information which must be consulted and sifted to find the desired end result.
The most commonly recognizable form of a search engine is a Web search engine which searches for information on the World Wide Web. Such Web search engines provide a standardized GUI interface (e.g., via a Web browser) that enables users to specify criteria about an item of interest, commonly referred to as a search query. The Web search engine then finds items that match the query. For example, in the case of a text search, the search query is typically expressed as a set of words that identify the desired concept that one or more documents may contain, such as, for example, “seafood restaurants in San Francisco” or “18 inch automobile tires”. The search engine will then return a list of items that it believes the best matches the specified query.
The list of items that meet the specified query is typically sorted, or ranked, in some regard so as to place the most relevant items most prominently. Ranking items by relevance, for example, from highest to lowest relevance, generally reduces the time users must spend sifting through the returned information. Alternatively, probabilistic rankings sort items based on measures of similarity, and sometimes popularity or authority. Another example would be Boolean rankings, which typically only return items which match the specified query exactly, without regard to order.
With the widespread emergence of the World Wide Web and the increasing power of the Web search engines, the general public has come to extensively rely upon web searches to obtain content and other information. In many cases, there is a surfeit of links for simple or popular queries. For instance, the query “digital camera” produces literally hundreds of millions of links with varying degrees of relevance on most search engines.
On the other hand, many queries have far fewer links. For example, some very specialized queries have so few relevant links that the links only go a few pages (e.g., with 20 or so items per page) and often are not very relevant to the user. Such specialized queries are often described as being in the tail of the distribution of search queries. In many such cases, users are incredibly frustrated by their inability to find the information they are looking for. As more and more people increasingly rely upon web searches to obtain the content, information, resources, etc. that they are looking for, the overall level of dissatisfaction will only increase for those users pursuing specialized queries.
Thus, there is a problem with the fact that there are certain queries, usually not very popular ones, that have relatively few relevant links. These queries are called “underserved”. What is required is a solution for identifying and intelligently handling underserved queries.